scholarly journals Energy Efficient VM Migration in Cloud Datacenter using Dolphin Echolocation Optimization with Tchebycheff Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 86-94 ◽  
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
System Performance ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Vm Migration ◽  
Multi Objective ◽  
Cloud Datacenter ◽  
Single Objective

The workload in cloud computing surroundings changes progressively delivering unwanted circumstances, for example, load unbalancing and minor usage. Virtual machine migration is an impressive plan in such circumstances inorder to improve system performance. With a specific end goal to give productive energy virtual machine migration is essential that migrates a running virtual machine without disconnecting the client or application. In any case, an algorithm in view of a single objective is generally familiar with to coordinate the migration process. Unexpectedly, there stay alive unconsidered variables affecting the migration process, for example, burden capacity, power utilization and resource wastage. We offer a multi-objective algorithm for obtaining VM migration by evaluating the multi objectives that are responsible for migration overhead. In this manner, we suggest a narrative relocation approach united by a Multi objective Dolphin Echolocation Optimization Algorithm (MO-DEOA) to assess several objectives. The aim is to efficiently obtain improved migration that concurrently diminishes power consumption by guaranteeing the performance of the system.

Three Misuse Patterns for Cloud Computing

2013 ◽  
pp. 36-53 ◽  
Author(s):  
Keiko Hashizume ◽  
Nobukazu Yoshioka ◽  
Eduardo B. Fernandez
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Point Of View ◽  
Resource Usage ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
On Demand ◽  
Computing Model ◽  
Is Security

Cloud computing is a new computing model that allows providers to deliver services on demand by means of virtualization. One of the main concerns in cloud computing is security. In particular, the authors describe some attacks in the form of misuse patterns, where a misuse pattern describes how an attack is performed from the point of view of the attacker. Specially, they describe three misuse patterns: Resource Usage Monitoring Inference, Malicious Virtual Machine Creation, and Malicious Virtual Machine Migration Process.

scholarly journals A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Jia Zhao ◽  
Yan Ding ◽  
Gaochao Xu ◽  
Liang Hu ◽  
Yushuang Dong ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Power Saving ◽  
Genetic Operators ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Vm Migration ◽  
Location Selection ◽  
Cloud Data

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy) of live VM migration for power saving and load balancing. We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). This paper has presented the specific design and implementation of MOGA-LS such as the design of the genetic operators, fitness values, and elitism. We have introduced the Pareto dominance theory and the simulated annealing (SA) idea into MOGA-LS and have presented the specific process to get the final solution, and thus, the whole approach achieves a long-term efficient optimization for power saving and load balancing. The experimental results demonstrate that MOGA-LS evidently reduces the total incremental power consumption and better protects the performance of VM migration and achieves the balancing of system load compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

scholarly journals A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Gaochao Xu ◽  
Yan Ding ◽  
Jia Zhao ◽  
Liang Hu ◽  
Xiaodong Fu
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Artificial Bee Colony ◽  
Power Saving ◽  
Bayes Theorem ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Vm Migration ◽  
Cloud Data ◽  
Bee Colony

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration’s ability and local exploitation’s ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

scholarly journals Efficient Virtual Machine Memory Transfer in Datacenter with optimal downtime

2019 ◽  
Author(s):  
Girish L
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Flow Chart ◽  
Key Factors ◽  
Virtual Machine Migration ◽  
Memory Transfer ◽  
Vm Migration ◽  
Host Machine ◽  
Machine Memory

Cloud computing is a technology which relies onsharing various computing resources instead of having localservers to handle applications. Cloud computing is driven byvirtualization technology. Virtual machines need migration fromone host to anther due to the presence of error or over loading orslowness in the current running host machine. Live Virtualmachine migration is the transfer of running virtual machinefrom one host to another without stopping the current runningtask. During this live virtual machine migration Downtime is oneof the key factors that have to be considered and assessed.Here we present detailed survey on what are the importance oflive virtual machine migration in cloud computing technologyand various techniques to reduce the downtime during livevirtual machine migration. The flow chart showing the steps usedin Pre copy approach for VM migration. And also we presentthe result of the comparison between the two virtual machinemigration environments, VMWare and Xen Server.

A Virtual Machine Migration Mechanism Based on Firefly Optimization for Cloud Computing

2020 ◽  
Vol 14 ◽  
Author(s):  
Shalu Singh ◽  
Dinesh Singh
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machine Migration ◽  
Vm Migration ◽  
Comparative Review ◽  
Migration Mechanism ◽  
Physical Node ◽  
Firefly Optimization ◽  
Data Centres

Background: Cloud computing is one of the prominent technology revolutions around us. It is changing the ways the consumer expends services, changing the ways the organization develop and run applications and is completely reshaping the old business models in multiple industries. Cloud service providers need large-scale data centres for offering cloud resources to users, the electric power consumed by these data centres has become a concrete and prudential concern. Most of the energy is dissipated in these data centres due to underutilized hosts which also subsidies to global warming. The broadly adept technology is virtual machine migration in cloud computing so our main focus is to save energy. Objective: Virtual machine (VM) migration can reap various objectives like load balancing, ubiquitous computing, power management, fault tolerance, server maintenance, etc. This paper presents an energy-oriented mechanism for VM migration based on firefly optimization that reduces energy consumption and no. of VM migrations to a great extent. Method: A Firefly optimization (FFO) oriented VM migration mechanism has been proposed which allocates tasks to the physical machines in cloud data centres. It strives to migrates high loaded VMs from one physical node to another physical node, which induces minimum energy consumption after VM migration. Results: The empirical result shows that the FFO based mechanism implemented in the CloudSim simulator performs better in terms of number of hosts saved up to 13.91% as contrast to First Fit Decreasing (FFD) algorithm and 8.21% as compared to Ant Colony Optimization (ACO). It reduced energy consumption up to 12.76% as compared to FFD and 7.78% as compared to ACO and ultimately lesser number of migrations up to 52.49% when compared to FFD and 44.51% as compared to ACO. Conclusion: The proposed scheme performs better in terms of saving hosts, reduced energy consumption and lesser number of migrations in contrast to FFD and ACO techniques. The research paper also presents challenges and issues in cloud computing, VM migration process, VM migration techniques, their comparative review as well.

Research on Trigger Strategy of Virtual Machine Dynamic Migration in Cloud Computing

2014 ◽  
Vol 926-930 ◽  
pp. 2084-2087
Author(s):  
Chun Ling An ◽  
Chun Lin Li ◽  
You Long Luo ◽  
Su Jie He
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Historical Data ◽  
Experimental Results ◽  
Migration Process ◽  
Virtual Machine Migration ◽  
Trigger Strategy ◽  
Double Threshold

According to the trigger strategy of virtual machine dynamic migration based on features closed in the process of dynamic migration of virtual machines in the cloud computing, this paper puts forward a double threshold trigger strategy using timing prediction based on historical data (DTS Algorithms). Then simulation on the CloudSim platform, and analyze the results of the experiment. Experimental results showed that in the system virtual machine migration using DTS algorithm can reduce the number of migration and the energy consumption during the migration process.

Sign in / Sign up

Export Citation Format

Share Document